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Excel 2016 for Engineering Statistics A Guide to Solving Practical Problems /
This book shows the capabilities of Microsoft Excel in teaching engineering statistics effectively. Similar to the previously published Excel 2013 for Engineering Statistics, this book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2016.
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| Edición: | 1st ed. 2016. |
| Colección: | Excel for Statistics,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 100 | 1 | |a Quirk, Thomas J. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Excel 2016 for Engineering Statistics |h [electronic resource] : |b A Guide to Solving Practical Problems / |c by Thomas J. Quirk. |
| 250 | |a 1st ed. 2016. | ||
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| 300 | |a XV, 248 p. 162 illus., 161 illus. in color. |b online resource. | ||
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| 490 | 1 | |a Excel for Statistics, |x 2570-4613 | |
| 505 | 0 | |a Introduction -- Sample size, mean, standard deviation, standard error of the mean -- Random number generator -- Confidence interval about the mean using the TINV function and hypothesis testing -- One-group t-test for the mean -- Two-group t-test of the difference of the means for independent groups -- Correlation and simple linear regression -- Multiple correlation and multiple regression -- One-way analysis of variance (ANOVA) -- Appendix A -- Appendix B -- Appendix C -- Appendix D -- Appendix E -- Index. | |
| 520 | |a This book shows the capabilities of Microsoft Excel in teaching engineering statistics effectively. Similar to the previously published Excel 2013 for Engineering Statistics, this book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical engineering problems. If understanding statistics isn't your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in engineering courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However,Excel 2016 for Engineering Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand engineering problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned. Includes 162 color screen shots to show the reader how to perform Excel steps correctly Suitable for undergraduates or graduate students At the beginning of his academic career, Prof. Tom J. Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service. He then taught Social Psychology, Educational Psychology, General Psychology, Marketing, Management, and Accounting at Principia College, and is currently a Professor of Marketing in the George Herbert Walker School of Business & Technology at Webster University based in St. Louis, Missouri (USA) where he teaches Marketing Statistics, Marketing Research, and Pricing Strategies. He has written 60+ textbook supplements in Marketing and Management, published 20+ articles in professional journals, and presented 20+ papers at professional meetings. He holds a B.S. in Mathematics from John Carroll University, both an M.A. in Education and a Ph.D. in Educational Psychology from Stanford University, and an M.B.A. from The University of Missouri-St. Louis. | ||
| 650 | 0 | |a Statistics . | |
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| 650 | 2 | 4 | |a Mathematical and Computational Engineering Applications. |
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